AN INTRODUCTION TO STATISTICAL LEARNING: WITH APPLICATIONS IN R torrent

Author: Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
Edition: 1st ed. 2013, Corr. 7th printing 2017 edition
Publication Date: August 12, 2013
Publisher: Springer
ISBN-10: 1461471370
ISBN-13: 978-1461471370
Pages: 426 pages
Format: pdf
Size: 11M

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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.

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